Fig 1.
Geographic location of the study area. Ontario is in east-central Canada and the country’s second-largest province by land area in km2.
Shape file source: Statistics Canada 2021, URL: https://www12.statcan.gc.ca/census-recensement/2021/geo/sip-pis/boundary-limites/index2021-eng.cfm?year=21. Map produced by authors using ArcGIS Pro version 3.0.3.
Table 1.
Explanatory variables.
Fig 2.
Distribution of Mpox by age group (2022-2024).
Fig 3.
Distribution of Mpox by gender (2022-2024).
Fig 4.
Bar chart of Mpox cases across the Ontario PHUs.
Fig 5.
Choropleth map of geographical distribution of Mpox incidence rate in Ontario (Incidence rate: case per 100,000 population) (PHU names are available in Fig 1).
Shape file source: Statistics Canada 2021, URL: https://www12.statcan.gc.ca/census-recensement/2021/geo/sip-pis/boundary-limites/index2021-eng.cfm?year=21. Map produced by authors using ArcGIS Pro version 3.0.3.
Fig 6.
Global spatial autocorrelation analysis of Mpox incidence rate in Ontario (global Moran’s I).
Shape file source: Statistics Canada 2021, URL: https://www12.statcan.gc.ca/census-recensement/2021/geo/sip-pis/boundary-limites/index2021-eng.cfm?year=21. Fig produced by authors using ArcGIS Pro version 3.0.3.
Fig 7.
Local spatial autocorrelation analysis of Mpox incidence rate in Ontario (local Moran’s I) (PHU names are available in Fig 1).
Shape file source: Statistics Canada 2021, URL: https://www12.statcan.gc.ca/census-recensement/2021/geo/sip-pis/boundary-limites/index2021-eng.cfm?year=21. Map produced by authors using ArcGIS Pro version 3.0.3.
Fig 8.
Getis-Ord Gi * hotspot analysis of Mpox incidence rate in Ontario (PHU names are available in Fig 1).
Shape file source: Statistics Canada 2021, URL: https://www12.statcan.gc.ca/census-recensement/2021/geo/sip-pis/boundary-limites/index2021-eng.cfm?year=21. Map produced by authors using ArcGIS Pro version 3.0.3.
Fig 9.
Spatial scan statistic calculated in SaTScan to detect significant Mpox local clusters.
Shape file source: Statistics Canada 2021, URL: https://www12.statcan.gc.ca/census-recensement/2021/geo/sip-pis/boundary-limites/index2021-eng.cfm?year=21. Map produced by authors using SaTScan version 10.1.3.
Fig 10.
Spatial scan statistic calculated in SaTScan to detect significant Mpox local clusters (visualized in ArcGIS Pro).
Shape file source: Statistics Canada 2021, URL: https://www12.statcan.gc.ca/census-recensement/2021/geo/sip-pis/boundary-limites/index2021-eng.cfm?year=21. Map produced by authors using ArcGIS Pro version 3.0.3.
Fig 11.
A Pearson correlation matrix illustrates the interdependence of the explanatory variables. Correlation coefficient values may be negative (-1) or positive (+1). If the correlation value is less than zero, it is weak, if it is larger than zero.
Table 2.
Goodness-of-fit based on test of overdispersion, Pearson and deviance.
Table 3.
Standard Poisson regression coefficients for factors influencing Mpox counts at PHU level in Ontario.
Table 4.
Model comparison (Criteria for assessing goodness- of-fit).
Table 5.
Generalized Poisson Regression coefficients for factors influencing Mpox incidence at PHU level in Ontario.
Fig 12.
Histogram of distribution of Mpox counts in Ontario PHUs.
Fig 13.
Interaction effect of population density, material deprivation and Mpox (a); population density, ethnic concentration and Mpox (b); population density, age and Mpox (c). The Mpox outcome is plotted as the contours. The blue areas denote lower counts of Mpox, while the redder areas denote higher counts, and the contours are labeled with the corresponding Mpox counts.